Lyapunov Exponents And Invariant Manifold For Random Dynamical Systems In A Banach Space


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Lyapunov Exponents and Invariant Manifolds for Random Dynamical Systems in a Banach Space


Lyapunov Exponents and Invariant Manifolds for Random Dynamical Systems in a Banach Space

Author: Zeng Lian

language: en

Publisher: American Mathematical Soc.

Release Date: 2010


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The authors study the Lyapunov exponents and their associated invariant subspaces for infinite dimensional random dynamical systems in a Banach space, which are generated by, for example, stochastic or random partial differential equations. The authors prove a multiplicative ergodic theorem and then use this theorem to establish the stable and unstable manifold theorem for nonuniformly hyperbolic random invariant sets.

Lyapunov Exponents and Invariant Manifold for Random Dynamical Systems in a Banach Space


Lyapunov Exponents and Invariant Manifold for Random Dynamical Systems in a Banach Space

Author: Zeng Lian

language: en

Publisher:

Release Date: 2008


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We study the Lyapunov exponents and their associated invariant subspaces for infinite dimensional random dynamical systems in a Banach space, which are generated by, for example, stochastic or random partial differential equations. We prove a multiplicative ergodic theorem. Then, we use this theorem to establish the stable and unstable manifold theorem for nonuniformly hyperbolic random invariant sets.

Random Dynamical Systems


Random Dynamical Systems

Author: Ludwig Arnold

language: en

Publisher: Springer Science & Business Media

Release Date: 2013-04-17


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Background and Scope of the Book This book continues, extends, and unites various developments in the intersection of probability theory and dynamical systems. I will briefly outline the background of the book, thus placing it in a systematic and historical context and tradition. Roughly speaking, a random dynamical system is a combination of a measure-preserving dynamical system in the sense of ergodic theory, (D,F,lP', (B(t))tE'lf), 'II'= JR+, IR, z+, Z, with a smooth (or topological) dy namical system, typically generated by a differential or difference equation :i: = f(x) or Xn+l = tp(x.,), to a random differential equation :i: = f(B(t)w,x) or random difference equation Xn+l = tp(B(n)w, Xn)· Both components have been very well investigated separately. However, a symbiosis of them leads to a new research program which has only partly been carried out. As we will see, it also leads to new problems which do not emerge if one only looks at ergodic theory and smooth or topological dynam ics separately. From a dynamical systems point of view this book just deals with those dynamical systems that have a measure-preserving dynamical system as a factor (or, the other way around, are extensions of such a factor). As there is an invariant measure on the factor, ergodic theory is always involved.